Cancer studies increasingly include medical imaging and measurements from multiple omics techniques. The main impetus for data integration is that, through these integrated data sets, an improved understanding of the underlying biology is obtained to be better able to predict a phenotype and to gain further insight into mechanistic aspects of the system at the molecular level. In this project we propose to develop innovative technologies to integrate metabolite data with multi-omic (metabolomics, proteomics and transcriptomics) and cancer imaging data to enable the detection of subtler and more complex associations among variables, with the medical imaging and the metabolome providing phenotypic measurements to which we can anchor the global measurements of the transcriptome and proteome. The proposed Multi-omics and Imaging Data Analysis System (MIDAS) will provide for the ingestion, annotation, quality control, and analysis of in vivo imaging data combined with ex vivo -omics data to advance research in cancer. MIDAS is aimed at helping the cancer and overall public health research communities advance faster towards the larger goal of precision medicine through valid and reliable data harmonization of metabolomics, transcriptomics, proteomics, radiomics and other imaging data.